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20232026
most citedFoundation Models for Time Series Analysis: A Tutorial and Survey

221 citations · 262 across the 16 of their papers we have counts for

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9 papers · 1 filter

q-bio.NC2026

Rethinking World Models for Biosignals

Xianglong Bao, Bosong Huang, Xiaoda Wang +4

World models promise to learn how systems evolve and respond to actions, enabling simulation, planning and decision-making. Bringing this promise to biosignals requires more than a…

cs.AI2026

TimeNet: An Extensible Unified Data Infrastructure for Next-Generation Temporal Foundation Models

Martin Maritsch, Timo Stoffregen, Thomas Kaar +36

Temporal Foundation Models (TFMs) aim to generalize across domains, datasets, and tasks. Yet, their development remains constrained by fragmented, task-specific data formats, annot…

cs.AI2026

EarthVerse: Benchmarking Scientific Agents Across Dynamic Earth Systems and Natural Hazards

Zhiqing Cui, Xinxiang Yin, Yihong Tang +11

Earth-system analysis reconstructs changing physical processes from observations that differ in source, scale, timing, and modality. Natural hazards make this work consequential be…

cs.AI2026

TimeSage-EV: A Live Benchmark for Agentic Time Series Analysis in Evolving Environments

Qingren Yao, Yaxuan Kong, Yuqi Nie +6

Time series analysis in high-stakes domains relies on recurring data releases, where new observations can alter the evidence base and the validity of later conclusions. Existing ti…

cs.LG2026

Aionoscope: Debugging Latent-State Accessibility in Time-Series Representations

Alexander Chemeris, Ming Jin, Randall Balestriero

Time-series models are often evaluated by what they can forecast or classify, but those scores do not show whether their representations preserve the process state a user may want…

cs.CL2026

TimeSage-MT: A Multi-Turn Benchmark for Evaluating Agentic Time Series Reasoning

Yaxuan Kong, Qingren Yao, Yuqi Nie +7

Time series data inform critical decisions across many real-world domains. While large language model (LLM) agents can analyze data through natural language and tools, it remains u…

cs.CL2026

SkillBrew: Multi-Objective Curation of Skill Banks for LLM Agents

Wentao Hu, Zhendong Chu, Yiming Zhang +6

Retrieval-augmented LLM agents increasingly rely on curated skill banks: collections of reusable textual principles that guide decision making on complex tasks. Existing approaches…

cs.LG2026

It's TIME: Towards the Next Generation of Time Series Forecasting Benchmarks

Zhongzheng Qiao, Sheng Pan, Anni Wang +7

Time series foundation models (TSFMs) are revolutionizing the forecasting landscape from specific dataset modeling to generalizable task evaluation. However, we contend that existi…

cs.LG2026

Breaking the Regional Barrier: Inductive Semantic Topology Learning for Worldwide Air Quality Forecasting

Zhiqing Cui, Siru Zhong, Ming Jin +3

Global air quality forecasting grapples with extreme spatial heterogeneity and the poor generalization of existing transductive models to unseen regions. To tackle this, we propose…